Qwen/Qwen3.5-27B:flex

Qwen3.5-27B is Alibaba's largest dense Qwen3.5 model, delivering near-frontier quality across reasoning, coding, and instruction following. It features a 262K token context window (extensible to 1M), thinking/reasoning mode, tool calling, multi-token prediction, and support for 201 languages. Best suited for production deployments and complex enterprise tasks requiring top-tier performance.

VisionReasoningTool callingJSON schema
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Specifications

Context window262K tokens
Max outputN/A
API typechat
AddedAug 14, 2026
Model ID
Data retentionNo
Used for trainingNo
Provider location🇺🇸 US

Benchmarks

Released 2026-02-24
GPQA Diamondreasoning
85.8%

Graduate-level physics, chemistry & biology questions designed to resist Googling.

Intelligence Indexreasoning
34.6%

Artificial Analysis Intelligence Index — a composite of multiple evaluations measuring overall model capability.

Scores are sourced from official model cards, Artificial Analysis, and public leaderboards. Benchmarks measure specific skills and do not capture every aspect of model quality. Always test on your own workload.

Pricing

Prices updated August 15, 2026
Input / 1M
$0.21
Output / 1M
$2.08
Cache write
N/A
Cache read
N/A
Estimated cost
100K input + 10K output$0.0416
1M input + 100K output$0.42
10M input + 1M output$4.16

Requesty charges exactly what the upstream provider charges, no markup, no per-request fees. Prompt caching and smart routing can reduce effective cost by 30-80%.

Quickstart

Drop-in compatible with the OpenAI SDK. Change the base URL, swap in your Requesty API key, and set the model to deepinfra/Qwen/Qwen3.5-27B:flex.

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from openai import OpenAI client = OpenAI( api_key="YOUR_REQUESTY_API_KEY", base_url="https://router.requesty.ai/v1", ) response = client.chat.completions.create( model="deepinfra/Qwen/Qwen3.5-27B:flex", messages=[ {"role": "user", "content": "Explain quantum computing in one paragraph."}, ], ) print(response.choices[0].message.content)

Other DeepInfra Inc. models

Frequently asked questions

How much does Qwen/Qwen3.5-27B:flex cost?
Qwen/Qwen3.5-27B:flex is priced at $0.21 per million input tokens and $2.08 per million output tokens when accessed via Requesty. Requesty charges exactly what the upstream provider charges, we don't add markup.
What is the context window of Qwen/Qwen3.5-27B:flex?
Qwen/Qwen3.5-27B:flex has a context window of 262K tokens. That's roughly 350 words of input you can fit in a single prompt.
How does Qwen/Qwen3.5-27B:flex perform on benchmarks?
Qwen/Qwen3.5-27B:flex scores 93.9% on τ²-Bench, 85.8% on GPQA Diamond, 39.5% on SciCode. See the full benchmark chart above for results across MMLU Pro, GPQA Diamond, SWE-Bench Verified, HumanEval, MATH, AIME, MMMU, and LiveBench.
What can Qwen/Qwen3.5-27B:flex do?
Qwen/Qwen3.5-27B:flex supports vision input, tool calling, extended reasoning, structured outputs (JSON schema). You can call it through any OpenAI-compatible client by pointing base_url to Requesty.
How do I use Qwen/Qwen3.5-27B:flex with the OpenAI SDK?
Install the OpenAI SDK, set base_url to "https://router.requesty.ai/v1", set your API key to your Requesty key, and set the model to "deepinfra/Qwen/Qwen3.5-27B:flex". The Quickstart above shows Python, JavaScript and cURL snippets.
Can I run Qwen/Qwen3.5-27B:flex through Requesty?
Yes. Qwen/Qwen3.5-27B:flex runs through Requesty's OpenAI-compatible API, served from DeepInfra Inc.. You do not host the model yourself: point base_url at Requesty, set the model to "deepinfra/Qwen/Qwen3.5-27B:flex", and requests are routed to the upstream provider with automatic failover. The same key gives you 600+ other models too.

Access Qwen/Qwen3.5-27B:flex through Requesty

One API key, 600+ models, OpenAI-compatible. No markup on provider prices, automatic failover, and smart caching built-in.